This disclosure relates generally to encoding data in machine-readable images, and more particularly to improving efficiency and robustness of data encoding and retrieval via use of a circular image.
Binary bit-strings—sequences of 1s and 0s—are commonly encoded in machine-readable images for a variety of purposes. These images can be displayed online and in the physical word, and scanned by camera-equipped devices, which then extract the encoded information. One common example is the QR code, which is used in advertising, payments, and a number of other fields. Encoding binary data in a machine-readable image allows information to be transmitted rapidly in the physical world without human users having to manually copy, record, or otherwise transfer the information by hand. Information transmitted in binary form includes verification codes, card PINs, and digital content links.
Currently available techniques for encoding information in an image, including QR codes, continue to suffer from reliability and accuracy issues. QR codes in particular need to be scanned by a camera-equipped device held in a particular orientation. If the captured image is rotated relative to the expected orientation, then the image can sometimes be unreadable. In everyday situations, such as at a store counter or any other unpredictable and noisy environment, efficiency and accuracy can be improved by using a rotationally-invariant image that can be scanned at any angle. Furthermore, this encoding scheme is more tolerant of distortion and scale than other encoding schemes, and its redundancy increases the fidelity of the scanning process.